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, statistics, and microbial community analyses Experience with machine learning approaches, including the ability to apply relevant statistical models and predictive analytics to biological datasets, is highly
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antigen receptor (CAR) T-cell therapies for cancer. In this role candidates will: Employ independent discretion and judgement in carrying out assignments within the predetermined research scope of the PI’s
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$35.00/ hour Type of Position Staff Position Time Status Full-Time Required Education BS is required, MS or PhD is preferred. Required Related Experience Prior experience in biological sciences Required
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contribute to the development of innovative, physiology/ machine learning-driven clinical solutions and decision support tools for critically ill patients, focusing on cardiovascular and respiratory monitoring
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machine learning. The project aims to develop AI methods for mesoscale structural biology, understanding how cellular macromolecules organize into higher-order structures. You will work in a team at Janelia
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. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
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of machine learning to the practical tools of deep learning, now available through modern foundation models. For the theory part, the selected candidate will work in close collaboration with
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: Modern machine learning approaches are increasingly exploited to automate and optimize fault detection and classification. We propose to investigate methods that improve diagnostics under under-represented
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collaboration with courts and partners across Switzerland. We are looking for a PhD Student in Law. This doctoral position is part of the SNSF-funded project “Responsible AI for the Swiss Judiciary” at ETH Zurich
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on entangled photons for shining light onto the interface of quantum physics and gravity? Can we exploit quantum photonics technology for novel quantum machine learning, quantum computing and quantum